A Support Vector Regression Method for Predicting the Release Characteristics of Harmful Elements in Coal Combustion
A technology of support vector regression and harmful elements, applied in the direction of measuring devices, fuel testing, instruments, etc., to achieve the effect of improving practicability, strong nonlinear regression modeling ability, and good application prospects
Active Publication Date: 2022-04-29
HUAZHONG UNIV OF SCI & TECH
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In the prior art, there have been relevant studies on the prediction of the relationship between coal industrial analysis data and calorific value, but the release characteristics of harmful elements are still in the basic research stage, and a method for predicting the release characteristics of harmful elements in coal is still needed method
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[0035] In the present embodiment, the coal quality analysis is analyzed with reference to the method of the national standard, and the result is based on the received basis of the coal, and the ash of the coal is divided into: A ar ; The content of each mineral element in coal ash is analyzed by X-ray fluorescence spectrometry (XRF), and the result is given in the form of mass fraction of oxide, respectively M ash Na ,M ash Mg ,M ash Al ,M ash Si ,M ash K ,M ash Ca ,M ash Fe .
[0036] A method for predicting release characteristics of harmful elements in coal by support vector regression method, wherein said harmful element is set as arsenic (As), comprising the following steps:
[0037] (1) Set magnesium, sodium, aluminum, silicon, potassium, calcium and iron as mineral elements, and make a table of relative fixed coefficients according to the relative size of the adsorption amount of mineral elements to harmful elements.
[0038] (s1) Continuously and stably generate...
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The invention belongs to the field of thermal power units, and more specifically relates to a method for predicting the release characteristics of harmful elements in coal by support vector regression, including the following steps: (1) making Relative fixed coefficient table; (2) select any known coal type, measure the mass percentage of ash in the known coal type, the mass percentage of mineral elements in coal ash and the mass concentration of harmful elements in coal; (3) Calculate the total fixed coefficient of harmful elements and the release index of harmful elements of the known coal; (4) establish the model of the release index; (5) predict the release index of the harmful elements in the coal to be tested. The invention can establish an accurate, simple and direct prediction model for predicting the release characteristics of harmful elements such as arsenic and lead in different coals, and is suitable for guiding the formulation of coal blending schemes for controlling the emission of harmful elements during coal blending and blending of large thermal power units.
Description
technical field [0001] The invention belongs to the field of thermal power units, and more specifically relates to a method for predicting the release characteristics of harmful elements in coal by a support vector regression method. Background technique [0002] Coal is the main primary energy source in my country. Harmful elements such as arsenic and lead enter the atmosphere in the gas phase during the coal combustion process and migrate to water bodies and soil. Although the content of harmful elements in coal is low, due to the huge amount of coal used in our country, and the harmful elements are still highly toxic at very low concentrations, they will cause serious harm to the environment. Existing particle emission control technologies are still unable to effectively control the emission of harmful elements such as arsenic and lead, so it is of great significance to develop new technical means to control the emission of harmful elements such as arsenic and lead. [0...
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IPC IPC(8): G01N33/22G06K9/62
CPCG01N33/222G06F18/2411
Inventor 张成袁昌乐许豪余圣辉陈鑫科方庆艳陈刚
Owner HUAZHONG UNIV OF SCI & TECH